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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Namboodiri, A.M. Jain, A.K. |
| Copyright Year | 2002 |
| Description | Author affiliation: Dept. of Comput. Sci. & Eng., Michigan State Univ., USA (Namboodiri, A.M.; Jain, A.K.) |
| Abstract | Automatic identification of handwritten script facilitates many important applications such as automatic transcription of multi-lingual documents and search for documents on the Internet containing a particular script. The increase in usage of handheld devices which accept handwritten input is creating a huge volume of handwritten data. We propose a method to classify words and lines in an online handwritten document into Arabic, Cyrillic, Devnagari, Han, Hebrew and Roman scripts. The proposed classification system, based on spatial and temporal features of the strokes, attained an overall classification accuracy of 86.5% at the word level on a dataset containing 13,379 words. The classification accuracy improves to 95% as the number of words in the test sample is increased to five and to 95.1% for complete text lines. |
| Starting Page | 736 |
| Ending Page | 739 |
| File Size | 273388 |
| Page Count | 4 |
| File Format | |
| ISBN | 076951695X |
| ISSN | 10514651 |
| DOI | 10.1109/ICPR.2002.1048081 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2002-08-11 |
| Publisher Place | Canada |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Natural languages Handheld computers Internet Personal digital assistants Computer science Application software Testing Portable computers Personal communication networks Information retrieval |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition |
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